Burdwan University Thalassemia Severity (BUTS) Scoring System: A numerical Method For Defining the Clinicopathological status of Thalassaemia Patient

Background{beta}-haemoglobinopathies are the most common monogenic disorders worldwide. They present with extreme clinical heterogeneity, which makes generalized therapeutic approaches often ineffective. Currently available risk stratification approaches are either too complicated to be deployed at a primary healthcare level or are limited in their applicability across the spectrum of haemoglobinopathies. All current systems also classify patients into the three categories of mild, moderate and severe, where the moderate category is not well-characterized in terms of their expected prognosis. MethodsThe current study proposes a severity scoring scheme, utilizing five clinical parameters, viz., steady-state average pre-transfusion haemoglobin, age at presentation, transfusion interval, palpable splenomegaly and growth retardation to classify patients of various {beta}-haemoglobinopathies into severe and non-severe categories. The study then proceeds to validate this scoring scheme on a clinically heterogeneous cohort of 224 Eastern Indian {beta}-thalassaemia and {beta}-haemoglobinopathy patients, and evaluate the predictive performance of the proposed scheme against a clinical standard. ResultsAll of the chosen parameters except steady-state haemoglobin display strong individual contribution to the final determination of severity, though steady-state haemoglobin conferred increased discriminatory power to the overall scheme. The proposed system achieved an accuracy of 94% against the clinical standard. ConclusionsThe proposed risk stratification strategy, being almost entirely empirically-determined, should possess wider applicability across the spectrum of {beta}-haemoglobinopathies than currently existing systems, and should also be more suitable than said systems for studying genotype-phenotype correlations especially within the Eastern Indian {beta}-haemoglobinopathy population.